The introduction of genomics has been instrumental in accelerating the pace of drug discovery. The genomic technologies have proved their value in finding novel drug targets. Further improvement in this area will provide more efficient tools resulting in faster and more cost efficient development of potential drugs.
The drug discovery process includes several steps: the identification of a potential biochemical target associated with disease, screening for active compounds and further chemical design, preclinical tests, and finally clinical trials. The efficiency of this process is still far from perfect: it is estimated that about 75% of money spent in the R&D process went to fund failed projects. Moreover, the later in the product development a failure occurs, the bigger are losses associated with this project. Thus it is important to eliminate early in the process future failures in order to reduce costs of the whole drug development process. Thus, the quality of the original molecular target becomes a decisive factor for cost-effective drug development.
One approach that promises to impact on the process of target identification and validation is transcription profiling. This method compares expression of genes in a specific situation: for example, between disease and normal cells, between control and drug-treated cells or between cells responding to treatment and those resistant to it. The information generated by this approach can directly identify specific genes to be targeted by a therapy, and, importantly, reveals biochemical pathways involved in disease and treatment. In brief, it not only provides biochemical targets, but at the same time, a way to assess the quality of these targets. Moreover, in combination with cell-based screening, transcription profiling is positioned to dramatically change the field of drug discovery. Historically, screening for a potential drug was successfully performed using phenotypic change as a marker in functional cellular system. For example, growth of tumor cells in culture was monitored to identify anticancer drugs. Similarly, bacterial viability was used in assays aimed at identifying antibiotic compounds. Such screens were typically conducted without prior knowledge of the targeted biochemical pathway. In fact, the identified effective compounds often revealed such pathways and pointed out the true molecular target, enabling subsequent rational design of the next generations of drugs.
Modern tools of transcription profiling can be used to design novel screening methods that will utilize gene expression in place of phenotypic changes to assess effectiveness of a drug. For example, some methods are described in U.S. Pat. Nos. 5,262,311; 5,665,547; 5,599,672; 5,580,726; 6,045,988 and 5,994,076, as well as Luehrsen et al. (1997, Biotechniques, 22:168-74; Liang and Pardee (1998, Mol Biotechnol. 10:261-7). Such approaches will be invaluable, for example, for drug discovery in the field of central nervous system (CNS) disorders such as dementia, mild cognitive impairment, depression, etc., where phenotypic screening is inapplicable, but where a transcription profile can be established and linked to particular disorders. Once again, the identified effective compounds will likely reveal the underlying molecular processes. This approach can also be instrumental for the development of improved versions of existent drugs, which act at several biochemical targets at the same time to generate a desired pharmacological effect. In such case the change in the transcriptional response may be a better marker for drug action than selection based on optimization of binding to multiple targets.
In addition to uses in drug development, transcriptional profiling and other measurements of nucleic acid presence or abundance can be used for diagnosis, for example, where expression, overexpression or lack of expression of a particular gene or set of genes correlates with a given disease state or predisposition. Similarly, where copy number (amplification, deletion or disruption) of a gene sequence at the chromosomal level correlates with a disease or disease predisposition, determination of DNA copy number in an individual or in a tissue or cell type can predict or diagnose that disease.
Common methods of transcription profiling are based on technology using DNA microarrays, for example, as reviewed in Greenberg, 2001 Neurology 57:755-61; Wu, 2001, J Pathol. 195:53-65; Dhiman et al., 2001, Vaccine 20:22-30; Bier et al., 2001 Fresenius J Anal Chem. 371:151-6; Mills et al., 2001, Nat Cell Biol. 3:E175-8; and as described in U.S. Pat. Nos. 5,593,839; 5,837,832; 5,856,101; 6,203,989; 6,271,957; and 6,287,778. The DNA microarray approach performs simultaneous comparison of the expression of several thousand genes in a given sample by assessing hybridization of the labeled polynucleotide samples, obtained by reverse transcription of mRNAs, to the DNA molecules attached to the surface of the test array.
The microarray approach screens the pool of genes presented in the microarray. The current printing methods allows placement of 10,000-15,000 genes on a single chip, which is essentially a number of genes expressed in a particular cell type. Given the diversity of cell types, it requires development of specific arrays for specific cell types. Microarrays tend to provide qualitative, rather than quantitative results.
The number of transcripts in a tissue sample is even higher than in a cellular sample and can exceed the capacity of a microarray.
Exogenous control involves the use of an artificially introduced nucleic acid molecule that is added, either to the extraction step or to the PCR step, in a known concentration. The concept of adding an exogenous nucleic acid at a known concentration in order to act as an internal standard for quantitation was introduced by Chelly et al. (1988) Nature 333: 858-860, which is specifically incorporated herein by reference. Therefore, utilizing a control fragment that is amplified with the same primers as the target sequence more accurately reflects target sequence amplification efficiency relative to the internal standard (see, for example, WO 93/02215; WO 92/11273.; U.S. Pat. Nos. 5,213,961 and 5,219,727, all of which are incorporated herein by reference). Similar strategies have proven effective for quantitative measurement of nucleic acids utilizing isothermal amplification reactions such as NASBA (Kievits et al., 1991, J. Virol. Methods 35: 273-86) or SDA (Walker, 1994, Nucleic Acids Res. 22: 2670-7).
Capillary electrophoresis has been used to quantitatively detect gene expression. Rajevic at el. (2001, Pflugers Arch. 442(6 Suppl 1):R190-2) discloses a method for detecting differential expression of oncogenes by using seven pairs of primers for detecting the differences in expression of a number of oncogenes simultaneously. Sense primers were 5′ end-labelled with a fluorescent dye. Multiplex fluorescent RT-PCR results were analyzed by capillary electrophoresis on ABI-PRISM 310 Genetic Analyzer. Borson et al. (1998, Biotechniques 25:130-7) describes a strategy for dependable quantitation of low-abundance mRNA transcripts based on quantitative competitive reverse transcription PCR (QC-RT-PCR) coupled to capillary electrophoresis (CE) for rapid separation and detection of products. George et al., (1997, J Chromatogr B BIOMED Sci Appl 695:93-102) describes the application of a capillary electrophoresis system (ABI 310) to the identification of fluorescent differential display generated EST patterns. Odin et al. (1999, J Chromatogr B Biomed Sci Appl 734:47-53) describes an automated capillary gel electrophoresis with multicolor detection for separation and quantification of PCR-amplified cDNA.
Omori et al. (2000, Genomics 67:140-5) measures and compares the amount of commercially purchased α-globin mRNA by competitive PCR in two independently reverse transcribed cDNA samples using oligo(dT) or oligo(dU) primers. The oligo(dT) or oligo(dU) primers share a 3′ oligo(dT) or oligo(dU) sequence and a 5′ common sequence. In addition the oligo(dT) or oligo(dU) primer for each sample also contains a unique 29 nucleotide sequence between the 3′ oligo(dT) or oligo(dU) sequence and the 5′ common sequence. After the synthesis of first strand cDNA, PCR is performed to amplify the cDNA using a gene-specific primer and a primer complementary to the common sequence which is labeled with a unique label. The amplified PCR products are then analyzed by spotting onto a detection plate of a fluorescence scanner.